@inproceedings{83548dfafc884eb3a23b1cf5c89c4214,
title = "Analysis of Facial Expressions for the Estimation of Concentration on Online Lectures",
abstract = "The present study aimed to develop a method to estimate the state of attention from facial expressions while students are in online lectures. We con-ducted an experiment to measure the level of attention based on reaction time to detect an auditory target, which was the disappearance of noise sound, while watching lecture videos, assuming that reaction time for the detection of contents-irrelevant noise is longer when learners are focusing attention more to the contents of the videos. We sought facial features that are useful for predicting the reaction time and found that reaction time can be estimated in some amount from facial features. This result indicates that facial expressions are useful for predicting attention state, or concentration level while attending lectures.",
keywords = "Attention, Facial Features, Online Lecture",
author = "Renjun Miao and Haruka Kato and Yasuhiro Hatori and Yoshiyuki Sato and Satoshi Shioiri",
note = "Publisher Copyright: {\textcopyright} 2023, IFIP International Federation for Information Processing.; IFIP World Conference on Computers in Education, WCCE 2022 ; Conference date: 20-08-2022 Through 24-08-2022",
year = "2023",
doi = "10.1007/978-3-031-43393-1\_31",
language = "English",
isbn = "9783031433924",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "343--348",
editor = "Therese Keane and Cathy Lewin and Torsten Brinda and Rosa Bottino",
booktitle = "Towards a Collaborative Society Through Creative Learning - IFIP World Conference on Computers in Education, WCCE 2022, Revised Selected Papers",
address = "Germany",
}